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ORFS-agent uses LLMs to optimize chip design parameters, improving efficiency

Researchers have developed ORFS-agent, a new system that uses Large Language Models (LLMs) to optimize integrated circuit design parameters. This agent iteratively tunes thousands of parameters, showing improvements in design metrics like wirelength and clock period compared to standard optimization methods. The system demonstrated up to a 2.7% improvement in co-optimization objectives and used 40% fewer iterations, with newer LLM backends like Sonnet 4.6 and Kimi K2.5 outperforming earlier versions. AI

IMPACT Introduces a novel LLM-based agent for optimizing complex chip design parameters, potentially improving efficiency and design metrics.

RANK_REASON Academic paper detailing a new LLM-based agent for chip design optimization.

Read on arXiv cs.AI →

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ORFS-agent uses LLMs to optimize chip design parameters, improving efficiency

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Academic paper detailing a new LLM-based agent for chip design optimization.
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Amur Ghose, Andrew B. Kahng, Sayak Kundu, Zhiang Wang ·

    ORFS-agent: Tool-Using Agents for Chip Design Optimization

    arXiv:2506.08332v3 Announce Type: replace Abstract: Machine learning has been widely used to optimize complex engineering workflows across numerous domains. In integrated circuit design, modern flows (e.g., register-transfer level to physical layout) involve extensive configurati…